Hello, mlpack community, Hope you all are doing well. First, let me introduce myself. I am Heet Sankesara from India. I am currently pursuing my CSE degree in BTech. I've been engaged with the mlpack community for 2 weeks and like to be part of it. I previously talked to Ryan Curtin and opened a PR(#1809 <https://github.com/mlpack/mlpack/pull/1809>). This is my first PR in this organization and I'll be glad if some of you review it. I am intending to understand the codebase in depth and like to contribute to it more. I like to interact with the community and become an active member here. I am planning to participate in this year's GSoC. I aim to implement three clustering algorithms namely Agglomerative Hierarchical Clustering, Deep Clustering for Unsupervised Learning of Visual Features <https://arxiv.org/pdf/1807.05520.pdf> and Quantum clustering <https://arxiv.org/pdf/1612.09199.pdf> and do the comparative analysis (with K-Means and GMM as a baseline) of them. This comparative analysis will be aimed at knowing the strength and weakness of each algorithm and what kind of data is good for which algorithm. Please review my GSoC proposal <https://docs.google.com/document/d/1eVpbLYu2q97WI_wv_ZHg9vtOmNcBvpQhWuGSJ9Au9sc/edit?usp=sharing> and give feedback. I am happy to talk about the proposal further. With best regards, Heet Sankesara
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